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Velma is Modulate’s Conversation Understanding model. It analyzes audio signals (tone, emotion, intent, and dozens of other acoustic cues) and words to capture the true intent and meaning behind a conversation. Use Velma to surface risks or specific “behaviors” in voice conversations, such as fraud, customer churn, and compliance violations. It ships with 150+ pre-configured behaviors covering common conversation topics and business use cases. Additionally, you can define your own by describing what to detect in a natural-language prompt. Every response also includes a conversation summary, emotion and accent detection, speaker identification, conversation topics, deepfake detection, sentiment, a diarized transcript, and more. The power of Velma is that you describe what you want to detect, and Velma uses audio signals to detect them.

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Build with Velma

Start from a detection package — a ready-made configuration that groups the conversation types, roles, and behaviors for a common use case. Explore what each detects, then download and adapt it.

Fraud Detection and Prevention

Catch social engineering, account-takeover attempts, and impersonation in customer conversations.

Agentic AI Guardrails

Keep AI voice agents on-policy: catch off-script, unsafe, or out-of-scope behavior.

Trust and Safety

Flag harassment, hate, and safety violations in live social and voice-chat audio.

Customer Retention

Surface churn signals, dissatisfaction, and save opportunities on every call.

Human Agent Welfare

Protect agents by detecting abuse, distress, and burnout indicators.

Compliance and Risk Monitoring

Catch disclosure gaps, compliance breaches, and risk events across regulated calls.

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Batch or streaming?

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What Velma produces

Behavior detection

Per-behavior verdicts with confidence scores and the specific clips that triggered each detection.

Conversation type

Classification of the conversation against the types you define — customer support, sales, interview, and more.

Participant roles

Per-speaker role assignments drawn from the roles you configure, resolved in real time as speakers are identified.

Topics

An aggregated list of the subjects discussed across the full conversation.

Topic sentiment

Per-speaker sentiment scores for each extracted topic, ranging from −1 (negative) to +1 (positive).

Summary

A free-form narrative summary of the conversation generated at end of stream.

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How it works

Velma (batch) is an HTTP POST endpoint at /api/velma-2-batch. Submit a complete audio file as multipart/form-data — the upload_file field carries the audio (up to 100 MB), and the config field carries a JSON-encoded BatchConfig or the literal string "default" to use Velma’s built-in defaults.Velma processes the full recording and returns a single JSON response containing all clips, role assignments, behavior detections, topics, topic sentiment scores, and a summary.
Use batch when you have a finished recording and want a complete analysis in one call — post-call QA, compliance review, or processing an uploaded file.

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How Velma differs from the other endpoints

Velma includes transcription as part of its output via Transcription options in your configuration. If transcription alone is what you need, the Transcription endpoints are the right choice.

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Next steps

Capabilities

Explore all of Velma’s analysis outputs and configuration options in detail.

Behaviors

Learn how to define the signals you want Velma to detect.